My PhD dissertation in French “Plani cation Distribuee dans les Systemes Multi-agents a l’aide de Processus Decisionnels de Markov” (these-chades03)

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I publish in several fields including artificial intelligence (AI). The preferred publication mode in AI is through selective peer-reviewed conference proceedings. AI publications and citations are not referenced by ISI or ResearcherID. For these reasons, I use google scholar.

  1. Chadès, I., McDonald-Madden, E., McCarthy, M.A., Wintle, B., Linkie, M. & Possingham, H.P. (2008) When to stop managing or surveying cryptic threatened species. Proceedings of the National Academy of Sciences of the United States of America, 105, 13936. (ERA A*, IF 9.7)

Threatened species become increasingly difficult to detect as their populations decline. Managers of cryptic threatened species face several dilemmas: if they are not sure the species is present, should they continue to manage for that species or invest the limited resources in surveying? We discovered optimal solutions to this problem and simple rules of thumb using POMDP. We applied our finding to the Sumatran tiger, whooping crane and Mexican spotted owl. This paper has been featured in The Australian, ABC Science and TREE by MacKenzie, D. I. (2009). I was recently contacted by the NGO SOS Rhino to provide management guidance for the critically endangered Sumatran rhinoceros.

2. Chadès, I., Martin, T.G., Nicol, S., Burgman, M.A., Possingham, H.P. & Buckley, Y.M. (2011) General rules for managing and surveying networks of pests, diseases, and endangered species. Proceedings of the National Academy of Sciences of the United States of America, 108, 8323-8328. (ERA A*, IF 9.7)

We use Factored POMDP to show how to prioritize management and survey effort across time and space for networks of susceptible–infected–susceptible subpopulations. We present simple and robust rules of thumb for protecting desirable, or eradicating undesirable, subpopulations connected in typical network patterns (motifs). We demonstrate that these rules can be generalized to larger networks. Results show that the best location to manage or survey a pest or a disease on a network is also the best location to protect or survey an endangered species. Our rules offer managers a practical basis for managing networks relevant to many significant environmental, biosecurity and human health issues. I am applying this work to help control Aedes albopictus, an invasive mosquito species in the Torres Strait Islands (Qld Health, DAFF, Biosecurity flagship).

3. Regan*, T.J., Chadès*, I. & Possingham, H.P. (2011) Optimal strategies for managing invasive plants in partially observable systems. Journal of Applied Ecology, 48, 76-85. (*contributed equally) (ERA A, IF 5.0)

We developed a POMDP to provide optimal management actions when we are uncertain about the presence of invasive plants. We applied the POMDP to branched broomrape Orobanche ramosa, a parasitic plant species at the centre of a national eradication campaign in South Australia. The likelihood of eradication diminishes as colonization risk increases, highlighting the importance of limiting colonization if eradication was to be achieved. In addition to its contribution to the management of invasive species, this paper is also used to teach POMDP to AI students at Oregon State University. I am applying this work to help control Aedes albopictus, an invasive mosquito species in the Torres Strait Islands (Qld Health, DAFF, Biosecurity flagship).

4.    Chadès, I., Carwardine, J., Martin, T.G., Nicol, S., Sabbadin, R. & Buffet, O. (2012) MOMDPs: a solution for modelling adaptive management problems. The Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), pp. 267-273. Toronto, Canada. (ERA A*)

In this paper, we made a significant contribution to AI and Ecology by providing a new and efficient method to tackle adaptive management under model uncertainty. Adaptive management is the principal tool for conserving endangered species under global change, yet adaptive management problems suffer from a poor suite of solution methods. We show how to overcome this limitation by using a mixed observability MDP. This paper won the AAAI Computational sustainability best paper award. AAAI is the top 2 conferences of AI. We are currently using this method to manage shorebird species utilizing the East Asian-Australasian flyway (S. Nicol, CSIRO Climate Adaptation Flagship).

5. Martin, T.G., Chadès, I., Arcese, P., Marra, P.P., Possingham, H.P. & Norris, D.R. (2007) Optimal conservation of migratory species. PLoS ONE, 2. (ERA A, IF 4.4)

We used dynamic optimization to address the problem of how to allocate resources for habitat conservation for a Neotropical-Nearctic migratory bird, whose winter habitat is under threat. We demonstrate that conservation strategies for migratory animals depend critically upon two factors: knowledge of migratory connectivity and the correct statement of the conservation problem. Our framework can be used to identify efficient conservation strategies for migratory taxa worldwide, including insects, birds, mammals, and marine organisms.

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